جست‌وجوی استاد و پژوهشگر

Aaron Sparksمشاهده پروفایل

استاد پژوهشی

• Remote Sensing
• Precision Forestry
• Wildland Fire Ecology
• +۱ مورد دیگر

Aaron Sparks, Ph.D., is Research Assistant Professor of Fire Ecology & Geospatial Data Analysis at the University of Idaho. His work integrates remote sensing, field ecology, and geospatial analysis to understand fire effects on forest ecosystems. Education: Ph.D. in Natural Resources from University of Idaho (2017) M.S. in Natural Resources from University of Idaho (2014) B.S. in Resource Conservation from University of Montana (2010) Research combines LiDAR, multispectral imaging, and field measurements to quantify fire impacts on tree mortality, forest structure, and regeneration patterns. Current projects include developing remote sensing protocols for assessing fire-induced tree mortality, evaluating drought-fire interactions on conifer recovery, and mapping wildfire risk in Mediterranean landscapes. His methods advance precision forestry applications through improved inventory techniques and mortality prediction models.

Benjamin Fraserمشاهده پروفایل

استادیار مهمان

• Geographic Information Systems
• Remote Sensing
• Spatial Data Science
• +۷ مورد دیگر

Benjamin Fraser serves as a Visiting Assistant Professor in the Department of Natural Resources and the Environment at the University of New Hampshire, where he directs the Basic and Applied Spatial Analysis Lab and acts as AmericaView State Coordinator. With over a decade of experience, he specializes in applying geospatial technologies—GIS, remote sensing, and Unpiloted Aerial Systems (UAS)—to natural resource management across scales from individual trees to multi-million-acre landscapes. His work bridges technical innovation with practical conservation needs for agencies like the NH Division of Forests and Lands. Dr. Fraser's research centers on spatial data science and geovisualization for forest ecology and environmental conservation. He develops cutting-edge UAS and deep learning methods to monitor forest health, track pest outbreaks like spongy moth, and assess water quality. His international consulting portfolio spans nine countries across three continents with organizations including USAID, Wildlife Conservation Society, and NASA's SERVIR-SEA, addressing challenges in sustainable development and wildlife conservation through interdisciplinary collaboration. Analysis of his 10 publications (2018-2025) reveals consistent innovation in UAS applications, with dominant themes in individual tree detection, early pest identification, and cyanobacteria monitoring. His work demonstrates increasing integration of deep learning algorithms with multispectral imagery to enhance accuracy for land managers, particularly in temperate forest ecosystems. No scientific awards are documented in the provided materials. Dr. Fraser teaches core courses in Geographic Information Systems (NR 658), Remote Sensing (NR 757/857), and Digital Image Processing (NR 759/859) but has no listed advisees or grant details. He leads the Basic and Applied Spatial Analysis Lab, which develops spatial analysis methodologies for natural resource challenges, and coordinates AmericaView's state-level geospatial initiatives to support New Hampshire's environmental management needs through technology access and training.

Baoxin Huمشاهده پروفایل

استاد

• Remote Sensing
• Geomatics Engineering
• LiDAR Data Processing
• +۵ مورد دیگر

Dr. Baoxin Hu is a Professor in Geomatics Engineering at York University's ESSE department since 2003. She leads airborne LiDAR and hyperspectral missions, focusing on vegetation canopy characterization and wetland ecosystems. Her research integrates multi-source remote sensing data for environmental monitoring, including DEM generation and permafrost analysis. She directs the Earth Observation Laboratory located in Petrie Halls. Education background includes prior visiting fellowships at the Canadian Space Agency. Research emphasizes algorithm development for 3D scene reconstruction, forest succession stage analysis, and EAB infestation detection. Key areas include spatial-temporal modeling, InSAR technology applications, and machine learning integration with geospatial data. Publications span LiDAR-based methods (e.g., boundary adjustment algorithms, individual tree crown delineation) to multi-source data fusion for carbon modeling. Active in developing CNN frameworks for land cover classification and environmental impact assessments. Collaborates on projects involving RADARSAT-2 data and MODIS time-series analysis for northern Ontario ecosystems.

Konstantinos Derpanisمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Data Science
• +۵ مورد دیگر

Konstantinos Derpanis is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University. He holds a BSc (Honours) in Computer Science from the University of Toronto (2000), an MSc and PhD in Computer Science from York University (2003, 2010). His doctoral work earned the CIPPRS Doctoral Dissertation Award 2010 Honourable Mention. Prior to York, he served as Associate Professor at Ryerson University (2012–2020) and was a postdoctoral researcher at the GRASP Laboratory, University of Pennsylvania (under Prof. Kostas Daniilidis). He currently serves as an Associate Editor for IEEE TPAMI and Area Chair for AAAI 2021, ICRA 2021, CVPR 2021, and ICCV 2021. His research focuses on computer vision with emphasis on motion analysis, human motion understanding, and applications in image processing and machine learning (including deep learning). Key interests include generative models, neural radiance fields, and vision-language systems. His work bridges theoretical advancements and practical applications in computational photography, 3D reconstruction, and AI-driven perception. Education: BSc (Honours), Computer Science, University of Toronto, 2000 MSc (Computer Science, York University, 2003, supervised by Prof. John Tsotsos & Prof. Richard Wildes) PhD (Computer Science, York University, 2010, supervised by Prof. Richard Wildes) Awards: CIPPRS Doctoral Dissertation Award 2010 Honourable Mention His recent research trends highlight contributions to neural radiance fields (NeRF), generative models, and vision-language systems. He explores techniques for robust scene representation, image/video editing via text instructions, and cross-modal retrieval. His work also addresses challenges in sensor fusion, temporal alignment, and interpretable AI. Dr. Derpanis has no listed grants or advisees in the provided texts but maintains active roles in academic service and conference organization.

Pieter G. Kikمشاهده پروفایل

دانشیار

• Nanophotonics
• Near-Field Optics
• Optical Engineering
• +۵ مورد دیگر

Pieter G. Kik is an Associate Professor in the Department of Optics & Photonics at CREOL, The College of Optics and Photonics, University of Central Florida. His research focuses on nanophotonics and near-field optics, with expertise in optical analysis tools for nanostructured devices. He leads a team investigating surface plasmon dispersion, erbium excitation enhancement in semiconductor nanocrystals, and plasmon-induced optical nonlinearities. Kik has been recognized for teaching excellence with awards from 2006 to 2014, including the 2006 Presidential Major Research Equipment Award and the 2007 Millionaire’s Club for research contributions. His research group employs advanced setups like near-field scanning optical microscopes, fiber-coupled microscopes, and variable-temperature photoluminescence systems. Key projects include manipulating plasmon dispersion in nanoscale films and developing transparent electrode geometries for light-trapping applications. Kik has advised multiple graduate students and contributed to over 15 peer-reviewed publications since 2018, with recent work on metasurface optofluidics and anti-biofouling silica nanoparticulate films. Awards: Excellence in Teaching (2013, 2014), TIP Award (2009), Millionaire’s Club (2007) Advising: 6 completed PhD/MS students, including Mengdi Sun (2022) and Fabricio Casco (current M.S.) Labs: Specializes in nanophotonics labs with cutting-edge optical characterization tools

John Sulikمشاهده پروفایل

دانشیار

• Biophysical Remote Sensing
• Energy & Sustainability
• Agronomy
• +۳ مورد دیگر

John Sulik is an Associate Professor in the Department of Plant Agriculture at the University of Guelph. His research focuses on biophysical remote sensing, energy & sustainability, agronomy, machine learning, GIS techniques, and unmanned aerial systems. B.S. Political Science, Florida State University M.S. Geographic Information Science, Florida State University Ph.D. Geography, Florida State University Dr. Sulik's research integrates geospatial technologies with agricultural and environmental applications. He has pioneered methods in spectral analysis for crop monitoring, spatial modeling for sustainability, and GIS-based humanitarian efforts. His recent publications highlight interdisciplinary work bridging remote sensing, agronomy, and energy policy. Notable contributions include advancements in spectral indices for canola crops, Bayesian causal networks for environmental data, and geospatial approaches to carbon inventory.

• Optical Communication
• Quantum Cascade Lasers
• Free-Space Optical Communication
• +۴ مورد دیگر

Rainer Martini is an Associate Professor of Physics and Associate Dean for Graduate Studies at the Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology. He leads the Ultrafast Laser Spectroscopy and Communications Laboratory, focusing on optical modulation, free-space communication, and infrared imaging. His research addresses bottlenecks in communication technology, such as all-optical modulation of lasers and detectors, achieving GHz-speed modulation in mid-infrared Quantum Cascade Lasers. Dr. Martini has pioneered mid-/far-infrared technology applications in spectroscopy, imaging, and communication, including weather-resistant quantum communication systems and novel broadband imaging devices covering UV to RF wavelengths. **Education**: PhD (1999) in Physics from RWTH Aachen; BS (1995) in Physics from University of Bonn. **Research Highlights**: First demonstration of coherent THz radiation amplification Stable mid-IR free-space optical link Broadband imaging system spanning 400nm (UV) to 100GHz (RF) **Awards**: 2011 NJ Inventor Hall of Fame Award, multiple teaching awards, and senior fellowships in Optica and SPIE. He has secured over $1.7M in grants, including leadership roles in ONR-funded projects like SeaQuAKE. **Administration**: Served as Physics Department Chair, Board of Trustees member, and Graduate Studies Committee Chair. Active in curriculum development, including creating SKIL laboratory courses and redesigning photonics curricula. **Patents**: 7 patents granted, including optical gyroscopes and 3D impedance imaging systems. Co-founded 'Predator-Vision' based on thermal imaging patents.

Brent Sealesمشاهده پروفایل

استاد

• Digital Heritage
• Computer Vision
• Manuscript Conservation
• +۲ مورد دیگر

Brent Seales holds the Stanley and Karen Pigman Heritage Science Chair and serves as Director of Graduate Studies for Data Science at the University of Kentucky College of Engineering. As Professor of Computer Science, he leads research in computational heritage science and medical imaging visualization. Research develops innovative methods for recovering and analyzing historical documents using non-invasive techniques like X-ray tomography and multispectral imaging. Current projects include virtual unwrapping of Herculaneum papyri, parchment codex analysis, and computational epigraphy. Medical applications focus on surgical visualization architectures and AI-enhanced diagnostic imaging for cardiac assessment. Publications demonstrate consistent advancement in 3D reconstruction methodologies, with recent emphasis on machine learning applications for cultural heritage preservation and medical interface design.

Jing Qinمشاهده پروفایل

دانشیار

• Mathematical Optimization
• Variational Image Processing
• Compressive Sensing
• +۳ مورد دیگر

Jing Qin is an Associate Professor in the Department of Mathematics at the University of Kentucky, within the College of Arts & Sciences. His research focuses on Mathematical Optimization, Variational Image Processing, Compressive Sensing, and computational analysis of imaging data. His work addresses challenges in signal recovery, tensor decomposition, hyperspectral imaging, and machine learning applications. Recent publications emphasize advancements in tensor recovery algorithms, hyperspectral band selection, and graph-based signal processing. These contributions highlight innovations in iterative methods, regularization techniques, and deep learning models for structural analysis and robotic systems. Qin’s research bridges theoretical optimization frameworks with practical applications in remote sensing, medical imaging, and computer vision. His articles reflect a strong focus on interdisciplinary solutions, combining mathematical rigor with computational efficiency. Despite no explicitly listed awards or grants, his prolific publication record underscores sustained scholarly impact. Further details are available via his faculty webpage: http://ms.uky.edu/~jqi229/ .

Mobashar Rehmanمشاهده پروفایل

مدرس ارشد

• Knowledge Management
• Digital Transformation
• Supply Chain Management
• +۳ مورد دیگر

Dr. Mobashar Rehman is a Senior Lecturer in Digital Business and Analytics at the School of Business, Faculty of Business and Law, Middlesex University, London. He previously held positions as Assistant Professor at Universiti Brunei Darussalam (2022) and Universiti Tunku Abdul Rahman, Malaysia (2012–2022). He earned a PhD in Knowledge Management from Universiti Teknologi PETRONAS, an MBA, and a BS in Computer Science. His research focuses on Knowledge Management, Digital Transformation, Supply Chain Management, and Cybersecurity, with over 63 publications and £182,845 in research grants. He teaches courses like Enterprise Resource Planning and Global Supply Chain Management. Research Interests: Knowledge Sharing in Software Engineering Digital Transformation Strategies Supply Chain Agility Cyber Hygiene and Information Security Sustainable Tourism Marketing STEM Education Gender Disparities Grants & Collaborations: Involved in grants exceeding £182k and international collaborations in joint research and publications. Supervises PhD student Rory Mc Connon. Recent Trends in Articles: Focuses on organizational support in knowledge sharing, social media in tourism, IT adoption in supply chains, and cybersecurity behaviors. Explores adaptive machine learning frameworks for IoT and image classification, emphasizing practical applications in dynamic environments.

Terrence Triccoمشاهده پروفایل

استادیار

• Synthetic Data Generation
• Smoothed Particle Hydrodynamics (SPH)
• High-Performance Computing
• +۶ مورد دیگر

Terrence Tricco is an Assistant Professor in the Department of Computer Science at Memorial University of Newfoundland, cross-appointed with the Department of Physics and Physical Oceanography. He chairs the Master's of Data Science program and leads the Simulation, Modeling and Synthetic Data Lab. His research focuses on synthetic data generation using deep learning, astrophysical smoothed particle hydrodynamics (SPH), and high-performance computing. Tricco is a development lead for the Phantom SPH code and creator of the Sarracen Python analysis package. He is Principal Investigator of the Centre for Analytics, Informatics and Research (CAIR), managing a high-performance computing cluster. Collaborations include Verafin (financial synthetic data) and VBHC-NL (healthcare analytics). Key research areas include multi-physics SPH algorithms, parallel computing optimization, and numerical analysis of SPH convergence. Tricco's work bridges computational science with applications in astrophysics, healthcare, and finance. Notable software contributions include Phantom (astrophysical SPH simulations), Sarracen (SPH visualization), and Framalytics (FRAM modeling integration). His lab emphasizes synthetic data generation for sensitive domains like healthcare and finance. Recent work explores generative AI for data synthesis and improving SPH method scalability on modern architectures.

Rohith Reddyمشاهده پروفایل

دانشیار

• Biomedical Imaging
• Medical Devices
• Photonics
• +۳ مورد دیگر

Dr. Rohith Reddy is Associate Professor and CPRIT Scholar in Cancer Research in Electrical and Computer Engineering at the University of Houston. He develops optical imaging technologies for biomedical diagnostics, with emphasis on cancer detection and point-of-care devices. Education includes: PhD in Bioengineering, University of Illinois at Urbana-Champaign Postdoctoral training at Harvard Medical School B.Tech/M.Tech in Electrical Engineering, IIT Madras Research focuses on mid-infrared spectroscopic imaging, optical coherence tomography, and nanophotonic platforms for detecting cancer biomarkers and infectious pathogens. Innovations include high-definition FT-IR imaging, micro-retroreflector assays, and tethered capsule endomicroscopy. Recent publications advance photothermal mid-infrared imaging for gynecologic cancer subtyping, dual-comb spectroscopy techniques, and computational methods for tissue analysis. Work bridges optical engineering with clinical applications. Awards include: FACSS Innovation Awards (2012, 2016) William F. Meggers Award Massachusetts General Hospital Research Award Patents cover optical imaging devices, endoscopic systems, and 3D reconstruction methods. Research funding includes CPRIT support for cancer diagnostic technology development.

Christophe Silienمشاهده پروفایل

استاد

• Material Science
• Nanotechnology
• Optics
• +۵ مورد دیگر

Christophe Silien is a Professor at the University of Limerick (UL), holding positions in the Bernal Institute and the Department of Physics. His research focuses on material science, nanotechnology, and biomedical engineering, with a strong emphasis on piezoelectric materials, nanorod assemblies, and bioelectrets. He leads interdisciplinary projects involving plasmonics, optoelectronics, and biomaterials. Key research areas include the development of light-emitting diodes, nanoscale material characterization via advanced microscopy techniques, and applications in biomedical devices. Silien collaborates widely, with contributions to topics like quantum dot biosensors, thermal imaging of defects, and plasmonic nanoparticle systems. His work intersects physics, engineering, and biology, addressing challenges in energy, healthcare, and advanced manufacturing. Notable projects include the study of piezoelectric effects in proteins and intervertebral discs, electrophoretic deposition of nanorod layers, and the design of hollow needle insertion models for medical applications. Silien’s research has produced over 118 publications, emphasizing experimental and computational approaches to material innovation.

• Artificial Intelligence
• Pattern Recognition
• Biometrics
• +۵ مورد دیگر

Venu Govindaraju is a SUNY Distinguished Professor and Vice President for Research and Economic Development at the University at Buffalo. He holds a joint appointment in the Department of Computer Science and Engineering within the School of Engineering and Applied Sciences. His research focuses on artificial intelligence, pattern recognition, and biometrics, with notable contributions to handwriting recognition, cybersecurity, and educational technology. Govindaraju leads the National AI Institute for Exceptional Education (funded by a $20M NSF grant), developing AI tools to screen children for dyslexia and dysgraphia. He also founded the Center for Unified Biometrics and Sensors (CUBS) and co-leads the Institute for Artificial Intelligence and Data Science (IAD) at UB. His work has revolutionized postal automation, digital libraries, and cybersecurity through CAPTCHA innovations. He has advised 47 doctoral students and holds key leadership roles in SUNY's AI initiatives and Empire AI, a $400M state consortium. Research Interests: AI for social good, handwriting analysis, biometric systems, educational AI applications, and cross-modal data fusion. His work bridges technical innovation with societal impact, addressing challenges in healthcare, education, and security. Awards: IEEE Technical Achievement Award (2010), ACM Fellow (2009), IEEE Fellow (2006), National Academy of Inventors (2015), SUNY's Person of the Year (2024). Labs/Initiatives: CUBS, IAD, National AI Institute for Exceptional Education, Empire AI. Grants: $20M NSF grant (2023), USPS-funded handwriting recognition projects, Lockheed Martin licensing agreements.

Frank Witmerمشاهده پروفایل

دانشیار

• Human-Environment Geography
• Remote Sensing
• Spatial Statistics
• +۵ مورد دیگر

Frank Witmer is an Associate Professor in the Department of Computer Science & Engineering at the University of Alaska Anchorage. His work integrates human-environment geography, remote sensing, and spatial statistics to analyze violent conflict and environmental changes. Education : Ph.D. (Geography, University of Colorado, Boulder, 2007), M.A. (Geography, University of Colorado, Boulder, 2003), B.S. (Mathematics & Computer Science, Tufts University, 1997). His research focuses on quantifying how human activities like war, population growth, and urbanization affect environmental conditions such as land use, deforestation, and climate. He employs advanced methods from spatial statistics, GIScience, and remote sensing to analyze sociodemographic and environmental change data, including violence and crime patterns. Additionally, he uses immersive visualization in the Planetarium and Visualization Theater (PVT) to study environmental changes in Alaska fisheries and coastal erosion. Recent projects examine climate variability's influence on conflict in sub-Saharan Africa and the spatial diffusion of violence in regions like the North Caucasus and Afghanistan-Pakistan. His teaching spans computer science, geomatics, statistics, and mathematical courses, including Introduction to GIScience, Data Structures, and Image Analysis using Google Earth Engine.